ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Glycogen synthase 1 (GYS1) is the rate-limiting enzyme responsible for glycogen synthesis in skeletal muscle, heart, brain, and other extrahepatic tissues, playing a central role in systemic energy homeostasis. The human GYS1 gene maps to chromosome 19q13.33, comprises 16 exons, and encodes a 737-amino-acid polypeptide that is highly conserved across mammals. GYS1 activity is subject to multilayered and precisely coordinated regulation. At the transcriptional level, the GYS1 promoter contains a hypoxia response element (HRE) that mediates HIF-1α-dependent induction under low-oxygen conditions, as well as a muscle-specific enhancer harboring MEF2 and MyoD binding sites that confers tissue-restricted expression. At the post-translational level, a hierarchical phosphorylation cascade serves as the primary activity switch: glycogen synthase kinase 3β (GSK3β) sequentially phosphorylates four C-terminal serine residues following casein kinase II priming, while protein kinase A (PKA) and AMP-activated protein kinase (AMPK) provide parallel inhibitory inputs at both N- and C-terminal sites. Dephosphorylation and reactivation are mediated by protein phosphatase 1 (PP1) through tissue-specific glycogen-targeting regulatory subunits such as PPP1R3A and PPP1R3B, which anchor PP1 to glycogen particles and direct its activity toward GYS1. The allosteric activator glucose-6-phosphate (G6P) binds at the dimer interface, simultaneously enhancing catalytic efficiency and promoting dephosphorylation susceptibility, thereby establishing a feed-forward activation loop that couples substrate availability to glycogen synthesis. Beyond phosphorylation, GYS1 is regulated by ubiquitination (mediated by the E3 ligase PJA1), acetylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification, and SUMOylation, which collectively modulate protein stability, subcellular localization, and protein-protein interactions. Epigenetic mechanisms, including CpG island methylation and histone acetylation dynamics, govern chromatin accessibility at the GYS1 locus, while muscle-specific microRNAs such as miR-1 and miR-206 fine-tune GYS1 expression at the post-transcriptional level. Dysregulation of GYS1 has been identified as a central pathogenic driver in a spectrum of human diseases. In inherited glycogen storage disorders—including Lafora disease, adult polyglucosan body disease (APBD), and Pompe disease—loss of upstream regulatory control leads to GYS1 hyperactivation and the accumulation of structurally abnormal or excessive glycogen, resulting in progressive neurodegeneration, myopathy, and multiorgan dysfunction. In type 2 diabetes mellitus (T2DM), impaired insulin signaling through the PI3K-AKT-GSK3β axis maintains GYS1 in a hyperphosphorylated inactive state in skeletal muscle, compromising postprandial glucose disposal and exacerbating hyperglycemia. In oncology, GYS1 exhibits context-dependent roles across multiple cancer types. In hepatocellular carcinoma, FMO2⁺ cancer-associated fibroblasts stabilize GYS1 by competitively inhibiting PJA1-mediated ubiquitination, and stabilized GYS1 subsequently activates NF‑κB/CCL19 signaling to promote tertiary lymphoid structure formation and enhance anti-PD-1 immunotherapy responsiveness. In clear cell renal cell carcinoma, GYS1 promotes tumor progression through non-canonical NF‑κB pathway activation via the scaffold protein RPS27A. In triple-negative breast cancer, GYS1 has been identified as a trigger of disulfidptosis and an activator of NF-κB signaling through non-enzymatic facilitation of IκBα degradation. In colorectal cancer, mitochondrial fission deficiency drives AMPK-dependent GYS1 upregulation and glycogen accumulation as a compensatory survival mechanism, while in cervical cancer, GYS1-maintained glycogen reserves fuel the pentose phosphate pathway to generate NADPH for ROS clearance, thereby conferring cisplatin resistance in cancer stem cells. Therapeutic strategies targeting GYS1 have gained substantial momentum across these disease contexts. For glycogen storage disorders, antisense oligonucleotides, small interfering RNAs (e.g., ABX1100), and small-molecule inhibitors (e.g., MZ-101) have demonstrated preclinical and early clinical efficacy in reducing pathological glycogen accumulation. For T2DM, pharmacological activation of GYS1 through GSK3β inhibition or enhancement of PP1-mediated dephosphorylation is being explored to restore insulin-stimulated glycogen synthesis. In cancer, GYS1-directed interventions—including targeted silencing to sensitize tumors to chemotherapy and immune microenvironment modulation to enhance immunotherapy—represent emerging precision oncology approaches. This review provides a comprehensive and integrated account of GYS1 gene structure, tissue-specific distribution, regulatory networks, and pathogenic roles in metabolic disorders and malignancies, with the aim of establishing a theoretical framework for the development of GYS1-targeted precision therapies.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Objective To elucidate the functional role and underlying mechanisms of the ribosome biogenesis factor BMS1 in neuroblastoma(NB)cellular proliferation.Methods We utilized the R2 genomics analysis and visualization platform to analyze the correlation between BMS1 expression levels and clinical characteristics of NB children.The BMS1 mRNA level in three human neuroblastoma cells SK-N-BE(2),BE(2)-C,IMR-32 and two normal cells hTERT RPE-1,IMR-90 was detected by real-time quantitative polymerase chain reaction(RT-qPCR).Two distinct small interfering RNA(siRNA)sequences were used to target BMS1 mRNA in NB cells SK-N-BE(2)and BE(2)-C,with normal cells hTERT RPE-1 serving as controls.We used RT-qPCR to quantify the mRNA levels of BMS1 and two key neuroblastoma-associated molecules(MYCN and p53).After transfection with siRNA,cellular proliferation was detected by various experimental approaches:crystal violet staining,real-time cell analysis(RTCA),colony-forming unit assay and immunofluorescence.Results By analyzing two independent neuroblastoma clinical cohorts(GSE85047/NRC-283 and Westermann-144 datasets),it was found that the BMS1 mRNA level in MYCN-amplified NB was significantly higher than that in MYCN-non-amplified NB(P<0.05).Furthermore,the overall survival rate of NB children in the BMS1 high-expression group was decreased(P<0.05).Consistent with these clinical observations,the BMS1 mRNA level in NB cells SK-N-BE(2),BE(2)-C and IMR-32 was significantly higher than that in normal cells hTERT RPE-1,IMR-90(P<0.05).The targeted transient knockdown of BMS1 in NB cell lines SK-N-BE(2)and BE(2)-C resulted in decreased intracellular MYCN mRNA expression levels(P<0.05),significantly reduced cell proliferation capacity and colony-forming ability(P<0.05).Immunofluorescence revealed that the expression of Ki-67,a proliferation marker,was decreased(P<0.05).At the molecular level,RT-qPCR showed that the p53 mRNA level was significantly elevated in the BMS1-knockdown groups(si BMS1-1#and si BMS1-2#)compared with the control group(P<0.05).However,transient knockdown of BMS1 had no significant impact on the proliferative capacity of normal cells hTERT RPE-1.Conclusion BMS1 expression was up-regulated in MYCN-amplified NB and negatively correlated with the prognosis of the NB children.Mechanistically,interfering with BMS1 expression may transcriptionally activate p53 in NB cells,thereby inhibiting their proliferative ability,while having minimal impact on normal cells growth kinetics.These findings suggest that BMS1 serves as an important proliferation driver in NB and is expected to be a promising therapeutic target for NB children,particularly MYCN-amplified pediatric patients.

The high cost,high loss and high increase of test reagents are the difficulties in the management of hospital health consumables.The case hospital to industry and financial integration mechanism,process reengineering theory as the basis for practicing reagent whole process cost control.Through effective data governance,a comparison relationship is established between revenue and expenditure.The standard cost method is utilized to identify potential areas for reduction,allowing for the determination of cost control targets.Subsequently,design process reengineering scheme and steps,so as to create a new reagent cost control process where hospital and enterprises work together,and a new method of cost settlement of fixed ratio of income and expenditure.Through dual-directional performance appraisal,the management results are solidified,enabling dual control and reduction of procurement costs and usage expenses.This approach enhances inspection efficiency,quality,and service while effectively mitigating associated risks.

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.

Objective:To develop the Motivation for Bedtime Procrastination Questionnaire for College Students(CS-MBPQ)and evaluate its validity and reliability.Methods:Based on literature analysis,interviews with severe bedtime procrastinators,and open-ended surveys with college students,the initial questionnaire was formed.A total of 389 college students were recruited to conduct item analysis and exploratory factor analysis.Additionally,691 college students were selected for confirmatory factor analysis,criterion validity testing,and internal consistency reliability analysis,and 132 of them were retested two weeks later.The subscale of behav-ioral intention from the Theory of Planned Behavior Questionnaire(TPBQ),Bedtime Procrastination Scale(BPS),and a self-made question for the frequency of bedtime procrastination were used as criterion tools.Results:The CS-MBPQ consists of 10 items,encompassing three factors:emotional need,external influence,and behavioral attitude,explaining 63.31％of the variance.Confirmatory factor analysis indicated that the three-factor structure model of CS-MBPQ fitted well(x2/df=4.90,RMSEA=0.07,CFI=0.96,TLI=0.94).The CS-MBPQ total scores and scores for each factor were positively associated with the score of intentions to sleep on time,BPS scores,and bed-time procrastination frequency(ICC=0.14-0.53,Ps＜0.05).The internal consistency reliabilities for CS-MBPQ and the three factors were 0.87,0.89,0.74,and 0.66,respectively,and the test-retest reliabilities(ICC)were 0.74,0.66,0.69,and 0.58,respectively.Conclusion:The Motivation for Bedtime Procrastination Questionnaire for College Students(CS-MBPQ)demonstrates good validity and reliability,which could be used as a tool to evaluate motivations for bedtime procrastination among Chinese college students.

microRNA(miRNA),as a short non-coding RNA molecule,regulates bone-immune signal and stress response through transcription,translation as well as the combination of shear process,exerting the effect of promoting angiogenesis and repairing damage bone;type H vessels play a role in the cou-pling of angiogenesis and osteogenesis in the formation of new bone and promoting bone regeneration at the defect site.In re-cent years,miRNA regulates hypoxia inducible factor 1α(HIF-1 α)/vascular endothelial growth factor(VEGF),Notch,plate-let-derived growth factor-BB(PDGF-BB),Wnt/glycogen syn-thase kinase-3 β(GSK3 β)to affect the migration,recruitment,proliferation and differentiation of endothelial cells(ECs)and osteoblast(OB),promote the coupling of H-type vessels and os-teoblasts to improve bone homeostasis,and then prevent and treat bone metabolic diseases.This article explains the role of miRNA in regulating H-type vascular osteogenic coupling to provide tar-gets and pathways for improving bone homeostasis.In addition,the active ingredients of traditional Chinese medicine affect the differential expression of miRNA to promote H-type angiogenesis and provide strategies for clinical prevention and treatment of bone metabolic diseases.

Objective To screen the prescription,preparation,quality evaluation of Ganoderma lucidum extract nano-emulsion(GLEN)and study its anti-skin aging effect.Methods The emulsifier and oil phase of the nano-emulsion were preliminarily screened by solubility method.The pseudo-ternary phase diagram method was used to screen the nano-emulsions,and the prepared GLEN were evaluated for quality in terms of the appearance,particle size,structure,drug loading,stability and skin safety.A mouse skin aging model was constructed by injecting D-galactose combined with ultraviolet radiation.GLEN was applied to the skin at the modeling site and investigated for their anti-skin aging efficacy.Results The optimal GLEN prescription was 30%polyoxymethylene castor oil,14.4%glycerol,11.1%medium chain triglycerides,and 44.5%water.GLEN was a dark brown and transparent liquid at room temperature,O/W type nano-emulsion with an average particle size(32.20±2.89)nm,polydispersity coefficient 0.38±0.03,zeta potential value(-4.05±0.27)mV.The content of Ganoderma lucidum polysaccharides was(36.35±0.55)mg·mL-1,and the content of Ganoderma lucidum triterpenes was(5.99±0.46)mg·mL-1,which possessed good stability.Pharmacodynamic experiments showed compared with the model group,the skin scores of mice in the GLEN group significantly improved(P﹤0.05),the water content increased(P﹤0.01),and the contents of SOD,GSH-PX and Hyp increased(P﹤0.05),while the content of MDA was decreased significantly(P﹤0.01).HE,Masson and Sirius crimson staining further indicated that the pathological changes in mice were alleviated to varying degrees in GLEN group.And GLEN had high safety for skin,could be applied to human body.Conclusion In this study,the prepared GLENs were homogeneous in appearance,stable in nature,and exhibited significant anti-aging effects on mouse skin.